The embodiments described herein relate generally to facial recognition and video analytics, and more particularly, to apparatus and methods for false positive minimization in facial recognition applications.
Increases in the availability and capability of electronic devices such as cameras, tablets, smartphones, etc. have allowed some people to take pictures and/or capture video of their experiences. For example, the inclusion and improvement of cameras in smartphones, tablets, and/or other similar devices have led to increases in those devices being used to take pictures (e.g., photographic data, image data, etc.) and videos (e.g., video stream data). While, it has become easier for some people to take pictures and/or videos of their experiences, in some instances, there can still be challenges in including the desired parties (including the person who would otherwise be taking the picture or video). Moreover, a person generally has to remember and/or have the chance to take the picture and/or video, and failing to do can result in a lost opportunity.
In some instances, venues and/or events such as sporting events, concerts, rallies, graduations, and/or the like have cameras that can take pictures and/or video of those in attendance. In some instances, however, analyzing, parsing, and/or otherwise making the pictures and/or video stream available can use a relatively large amount of resources, can be inaccurate, and/or can fail to provide associated contextual data or the like. More specifically, in some instances, it can be difficult to verify that a particular person detected in a picture, was actually in the location captured in the picture, due to false positives obtained from using facial recognition alone to identify people in pictures.
Thus, a need exists for improved apparatus and methods for using contextual and location data for minimizing false positives at, for example, public events.